心脏病学
舒张期
医学
内科学
血压
人工智能
计算机科学
作者
David Lehmann,Bruna Gomes,Niklas Vetter,Olivia Braun,Ali Amr,Thomas Hilbel,Jens Müller,Ulrich Köthe,Christoph Reich,Elham Kayvanpour,Farbod Sedaghat-Hamedani,Manuela Meder,Jan Haas,Euan A. Ashley,Wolfgang Rottbauer,Dominik Felbel,Raffi Bekeredjian,Heiko Mahrholdt,Andreas Keller,Peter Ong
标识
DOI:10.1016/s2589-7500(24)00063-3
摘要
With increasing numbers of patients and novel drugs for distinct causes of systolic and diastolic heart failure, automated assessment of cardiac function is important. We aimed to provide a non-invasive method to predict diagnosis of patients undergoing cardiac MRI (cMRI) and to obtain left ventricular end-diastolic pressure (LVEDP).
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